Application of response surface methodology in optimizing simultaneous extraction of multiple mycotoxins in maize via QuEChERS

Abstract

Abstract Several methods have been developed for the analysis and detection of mycotoxins in food; however, they do not make use of critical statistics and mathematical tools for precise optimization. The goal of this study was to use a central composite design (CCD) to find the true optimum values for acetonitrile percentage MeCN (%), formic acid percentage FA (%), extraction time, and salt addition in the QuEChERS-LC-MS/MS method for extracting certain mycotoxins. Data analysis of full factorial screening experiments revealed that MeCN (%), FA (%), and extraction time significantly affected the analyte recovery. Analysis of variance, coefficient tables, and surface plots from CCD showed the relative interactions of factors and the statistical significance of the model. The P values from the lack of fit test ranged from 0.137 to 0.467, which indicated an insignificant lack of fit. A composite desirability function of 0.91 was found for the method, and the optimum conditions were found to be 0.1% (v/v) FA in 80.2% MeCN for 74 minutes. To demonstrate applicability, method validation was carried out according to Commission Implementing Regulation 2021/808. Recoveries ranging from 85.45–113.70% and CVs below 15% were obtained. All R2 values were above 0.98, and LOQs ranging from 0.33 to 60.45 µg/Kg were recorded. This method was tested on twenty maize samples collected from markets in Botswana. Thirteen samples had detectable mycotoxins, and two had levels of AFB1 above the maximum permitted level by the European Union (EU). This indicates the possibility of exposure for Botswana to high levels of AFB1, the most toxic of mycotoxins.